@defi_Boo
Account based inHong Kong
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Guru🧘♂️. Research intern.
Frankfurt on the Main, Germany
Joined April 2021
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Boo retweeted
研究半天别人是怎么能报价比我们低的，最后发现是靠骗。真的是大无语。
报价报低价，实际无法成交。全靠滑点设得大的用户成交
而且这"个别"做市商还是 wintermute，币圈最大的做市商也靠这挣钱？不怕有人告他们吗？
截图来自 OKX 聚合器文档
Dream life. I am considering London or New York in the coming year as a visiting scholar or a research assistant.
Thanks to AI, I can explore any research field of my interest even if I don't have any related training.
It was surreal to see my academic adventures on the front page of the @nytimes
Here’s how I built Crimson Education almost entirely while at universities:
Good take...
招新人来磨合是挺让人头秃的，所以之前我带团队的时候都喜欢去招自己之前用过的人。他们的能力不一定强，但起码稳定，沟通过程不会出错。
但毕竟这也不是个事。
AI时代，我可能也更倾向于找talent足够高的人去合作：
1. 很多问题是逻辑问题和能力问题。能力强的人，可以在透明的环境下一起合作；而且一些道德/法律问题，本质上也是一种逻辑选择。
2. talent的浓度很重要，几个聪明人一起做事，会比一个聪明人带一群臭皮匠交付的东西好很多。
3. ai时代让很多dirty/重复的脑力工作释放了出来。
OneKey 创始人：面试通过后先付费做实战测试
OneKey 创始人 @ohyishi 在 Binance 访谈中表示，面试通过后不会直接入职，而是先付费让候选人完成实战测试，必要时进入带薪磨合期。
测试通常持续两三天，较难的任务可能需要一周，用于观察候选人的解题思路、交付质量及沟通方式，同时让候选人提前了解未来同事与公司的工作方式。
来源：BN
卧槽
跟我写论文一模一样
之前干了两篇论文（一篇接收，一篇等结果）
就跟工具人一样，只知道点回车，验收的话，因为结果就比较简单，基本不用咋验收，把我做emo了
后面换到偏应用数学（运筹优化方向），才算找到了点研究的价值和意义，起码要手搓验证和理解，才能让ai继续干下一步活。
I am done with this shit. It is over. The state of engineering right now is horrible. It has been half a month since I started a new role at a big company. Nobody knows anything here. The specs, code, tests, PRDs, tickets, resolution of those tickets, reports, etc., everything is made by Claude Code. Nobody on my team likes this. They are being forced to ship as much as they can. I have heard multiple times from higher management that pushing code is not a bottleneck, so why are we slow? People are working 12 to 13 hours a day just to press enter. Nobody is reading anything. Humans in corporate are doing nothing on their own. Everyone, literally everyone, from an L1 to an L7 engineer here is doing the same thing. Talk to Claude. There is no sense of victory. Nobody is resolving bugs. In reality, nobody is thinking anymore. Everything is done by LLMs. It is so soul-sucking. I would not mind it, to be honest, if we were at least given the time to check out the code and see what is going where. But no, the goal is to just ship. No matter what happens.
Dov是一个充满干劲和热情的小伙子
总是先埋头干活和出方案
做视频创作很好啊，强烈支持，最好是做长一些的视频。
不过科技编年史的体裁不一定好做，印象中很少看到类似的长视频。主要是能体现自己的热情是最重要的，其他倒还好。
一般历史类的长视频都会有相关书籍，科技编年史的文本不太好找。
《朱元璋的帝王之路：把心打磨成铁石 》
一篇当年随手写的旧文, 感觉还不错。打磨成铁石是为了防止发疯, 哈哈哈哈哈
paragraph.com/@0xgw/2jQT66M5…
惊呆了
or论文烧token简直起飞
智力门槛： OR > CS > IS.
果然还是得选方向，没做or之前，我的cursor pro就够用。做了or后, claude max + 50u credit 都不够用
感觉做什么方向的研究都充满着struggle
实证方向的商科研究：
1. interesting findings/phenomenon -> theoretical development -> dataset support. Fail: the dataset is never enough or clean.
2. dataset -> theretical mapping -> findings. Fail: the findings have always been studied previously.
计算机文章：
1. propose an architecture -> run SOTA experiments. Fail: can't reach the SOTA
2. have a SOTA result -> mapping an architecture. Fail: nothing new in the architecture.
应用数学方向（OR/Engineering Operation)：
1. Find a phenomenon -> explain/optimize it using mathematical proofs. Fail: nothing new in the proof development.
2. Propose a model -> apply the model in a case. Fail: no case, no data.
对比下来，还是偏数学好一些，起码是个智力锻炼。前面两个累死累活, 做到怀疑人生，也是在抽盲盒。
Boo retweeted
Twenty-five Fields Medal winners have published a joint declaration warning about what they see as a severe misalignment between AI companies and the mathematics community.
Boo retweeted
Terence Tao made a very powerful point:
“In most cases in pure mathematics, the problems are posed not because we desperately want the solution to these problems in and of themselves, but because we have seen from past experience that human-directed efforts to solve these problems tend to spur further development of the field through the efforts to solve such problems, and then to digest any partial or complete solutions that emerge for further insights.
Prematurely solving the problem by purely AI-powered methods—particularly without full transparency into the solution process—can contaminate this process to the point where it actually becomes a net negative for the progress of mathematics as a whole.”
I’ve been following Terence Tao for like 20 years, and I have always been impressed by the clarity of his thinking.
This clarity stands out even more in this difficult moment, as AI labs turn mathematics into a battleground in their race for supremacy.
In this race, they risk damaging one of humanity’s highest intellectual endeavours.
